Business Domain Modelling using an Integrated Framework

This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modelling Language (UML), and an implementation pattern known as “Naked Objects”. This framework have been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study “Information Retrieval System for academic research” is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modelling. The framework is overviewed and justified as multimethodology using Mingers multimethodology ideas

A study of requirements engineering practices among software developers at UUM Information Technology (UUMIT)

Requirements Engineering (RE) is a systemic and integrated process of eliciting, elaborating, negotiating, validating and managing the requirements of a system in software development project. UUM has been supported by various systems in academic, administrative, students’ affair and many others. Most of the current systems are developed and maintained by the Information Technology Department (UUMIT). The aim of this study is to review the current requirements engineering practices and proposing requirements engineering practices during software development at UUMIT. The outsourcing of software development is rapidly growing because of its allied benefits in the limited resources of the organizations. The main problem that is discussed in this research is the lack of studies that support software development activities at the Information Technology department (UUMIT). The study used quantitative methodology and systematic literature review to answer research questions. The main significance of this study is helping educational institutes to produce quality software development and saving cost and time by implementing requirements engineering practices. In addition to that, the study contributes to UUM by identifying the activity needed for software development so that the management is able to allocate budget to provide adequate and precise training as well as seminars for the software developers. The researcher investigated three variables; Requirements Description, Requirements Development (Requirements Elicitation, Requirements Analysis and Negotiation, Requirements Validation), and Requirement Management. The results from the survey showed that the current practice of requirement engineering in IT department of UUM is encouraging, but need for further development because most of RE practices associated with requirement development and requirement management are achieved on a regular basis and not frequently. The researcher recommended providing effective training programs for UUMIT staffs on RE practices and increases their understanding on system requirements using RE practices to develop better systems for the university. Further investigation is required in the future to understand the effect of other RE practices on software developmen

Principles for data analysis workflows

Traditional data science education often omits training on research workflows: the process that moves a scientific investigation from raw data to coherent research question to insightful contribution. In this paper, we elaborate basic principles of a reproducible data analysis workflow by defining three phases: the Exploratory, Refinement, and Polishing Phases. Each workflow phase is roughly centered around the audience to whom research decisions, methodologies, and results are being immediately communicated. Importantly, each phase can also give rise to a number of research products beyond traditional academic publications. Where relevant, we draw analogies between principles for data-intensive research workflows and established practice in software development. The guidance provided here is not intended to be a strict rulebook; rather, the suggestions for practices and tools to advance reproducible, sound data-intensive analysis may furnish support for both students and current professionals

A Dataset and Analysis of Open-Source Machine Learning Products

Machine learning (ML) components are increasingly incorporated into software products, yet developers face challenges in transitioning from ML prototypes to products. Academic researchers struggle to propose solutions to these challenges and evaluate interventions because they often do not have access to close-sourced ML products from industry. In this study, we define and identify open-source ML products, curating a dataset of 262 repositories from GitHub, to facilitate further research and education. As a start, we explore six broad research questions related to different development activities and report 21 findings from a sample of 30 ML products from the dataset. Our findings reveal a variety of development practices and architectural decisions surrounding different types and uses of ML models that offer ample opportunities for future research innovations. We also find very little evidence of industry best practices such as model testing and pipeline automation within the open-source ML products, which leaves room for further investigation to understand its potential impact on the development and eventual end-user experience for the products

Modelo de evaluación del potencial de desarrollo, investigación e innovación basado en software libre, en programas académicos de Ingeniería de Sistemas– El Framework PDII

This paper describes a model to evaluate the potentialof development, investigation and invention inan academic program basing this potential, in thefreeware philosophy. This proposal focuses on tocomputer sciences academic programs and himselfdivide in three areas of evaluation to determinethe three aspects that is development, investigationand invention. The first area of evaluation is thecomputational applications scene that support thework of both professors and staff of the academicprogram, the second the academic sector determinesthe potential of professors to innovate in theiracademic activities of his training in free software,finally evaluates the research area that determines theproductivity in freeware of the academic program.Este articulo describe un modelo para evaluar elpotencial de desarrollo, investigación e innovaciónde un programa académico basando dichopotencial, en la filosofía del Software Libre (SL).Esta propuesta se enfoca a programas académicosen ciencias de la computación y se divide en tresáreas de evaluación para poder determinar los tresaspectos es decir, el desarrollo, la investigación yla innovación. La primer área de evaluación es elescenario de aplicaciones computacionales queapoyan el trabajo de los docentes y administrativosdel programa académico, la segunda es elsegmento académico que determina el potencialde los docentes para innovar en sus actividadesacadémicas según su preparación en software libre,finalmente se evalua el área de investigación quedetermina la productividad en software libre delprograma académico

WLAP the Web Lecture Archive Project: The Development of a Web-Based Archive of Lectures, Tutorials, Meetings and Events at CERN and at the University of Michigan

This paper summarizes the results of a project to develop an electronic repository of "content-rich" lectures, talks, and training activities on the World-Wide Web. The work was carried out from July 1999 to July 2001 by a collaboration consisting of the University of Michigan ATLAS Collaboratory Project, the University of Michigan Media Union, the CERN HR Division, supported by the CERN IT and ETT Divisions and the CERN Academic and Summer Student Programs. In this document, we describe the software application chosen to synchronize the slide presentations to the video recordings, provide technical solutions to the various recording and archival challenges encountered during the project, and propose a set of research and development issues we feel merit further investigation. We also present the concept of a "Lecture Object" and suggest the adoption of standards so that lectures at multiple institutes can be seamlessly shared and incorporated into federated databases world-wide

The Impact of Agile Methodology on Software Team’s Work-Related Well-Being

Agile methodology is people-oriented.However, little evidence demonstrates the methodology effectiveness on humanistic aspects.Work-related well-being is measured to what extent the agile methodology can give impact on anxiety, contentment, depression, and enthusiasm level among software engineering (SE) teams.This paper aims to investigate empirically the effect of agile methodology on software development team’s work-related well-being.To achieve this goal, a comparison study was carried out in an academic setting. A quantitative approach using statistical analysis was used to investigate the effect. Results showed that agile does not significantly affect work-related well-being.Nonetheless, the team that is able to apply the agile practices as closely as possible experienced higher level of enthusiasm during software project.This study provides additional empirical data in software engineering research and practices specifically on human aspects.Further investigation needs to be carried out on the software projects with higher task complexity

Bridging the Gap Between Research and Practice: The Agile Research Network

We report an action research-oriented approach to investigating agile project management methods which aims to bridge the gap between academic research and agile practice. We have set up a research network of academics from two universities, through which we run focussed project-based research into agile methods. Organisations are invited to suggest an ‘agile challenge’ and we work closely with them to investigate how challenge affects them. Our approach is both academic and practical. We use appropriate research methods such as interviews, observation and discussion to clarify and explore the nature of the challenge. We then undertake a detailed literature review to identify practical approaches that may be appropriate for adoption, and report our findings. If the organisation introduces new practices or approaches as a result of our work, we conduct an academic evaluation. Alternatively, if we uncover an under-researched area, we propose undertaking some basic research. As befits the topic, we work iteratively and incrementally and produce regular outputs. In this paper we introduce our approach, overview research methods used in the agile research literature, describe our research model, outline a case study, and discuss the advantages and disadvantages of our approach. We discuss the importance of producing outputs that are accessible to practitioners as well as researchers. Findings suggest that by investigating the challenges that organisations propose, we uncover problems that are of real relevance to the agile community and obtain rich insights into the facilitators and barriers that organisations face when using agile methods. Additionally, we find that practitioners are interested in research results as long as publications are relevant to their needs and are written accessibly. We are satisfied with the basic structure of our approach, but we anticipate that the method will evolve as we continue to work with collaborators

Bridging the gap between research and agile practice: an evolutionary model

There is wide acceptance in the software engineering field that industry and research can gain significantly from each other and there have been several initiatives to encourage collaboration between the two. However there are some often-quoted challenges in this kind of collaboration. For example, that the timescales of research and practice are incompatible, that research is not seen as relevant for practice, and that research demands a different kind of rigour than practice supports. These are complex challenges that are not always easy to overcome. Since the beginning of 2013 we have been using an approach designed to address some of these challenges and to bridge the gap between research and practice, specifically in the agile software development arena. So far we have collaborated successfully with three partners and have investigated three practitioner-driven challenges with agile. The model of collaboration that we adopted has evolved with the lessons learned in the first two collaborations and been modified for the third. In this paper we introduce the collaboration model, discuss how it addresses the collaboration challenges between research and practice and how it has evolved, and describe the lessons learned from our experience

Climate action for health and wellbeing in cities: a protocol for the systematic development of a database of peer-reviewed studies using machine learning methods [version 1; peer review: awaiting peer review]

Home Browse Climate action for health and wellbeing in cities: a protocol for... ALL METRICS 99 VIEWS 11 DOWNLOADS Get PDF Get XML Cite Export Track Email Share ▬ STUDY PROTOCOL Climate action for health and wellbeing in cities: a protocol for the systematic development of a database of peer-reviewed studies using machine learning methods [version 1; peer review: awaiting peer review] Kristine Belesova https://orcid.org/0000-0002-6160-50411, Max Callaghan https://orcid.org/0000-0001-8292-87582, Jan C Minx https://orcid.org/0000-0002-2862-01782, Felix Creutzig2, Catalina Turcu https://orcid.org/0000-0003-2663-25863, Emma Hutchinson1, James Milner1, Melanie Crane https://orcid.org/0000-0002-3058-22114, Andy Haines https://orcid.org/0000-0002-8053-46051, Michael Davies5, Paul Wilkinson1 Author details 1 Department of Public Health, Environments and Society and Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK 2 Mercator Research Institute on Global Commons and Climate Change, Berlin, 10829, Germany 3 Bartlett School of Planning, University College London, London, WC1H 0QB, UK 4 Charles Perkins Centre, Sydney School of Public Health, University of Sydney, Sydney, Australia 5 Bartlett School Environment, Energy & Resources, University College London, London, WC1H 0QB, UK Kristine Belesova Roles: Conceptualization, Data Curation, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Max Callaghan Roles: Data Curation, Investigation, Methodology, Software, Writing – Review & Editing Jan C Minx Roles: Conceptualization, Investigation, Methodology, Software, Writing – Review & Editing Felix Creutzig Roles: Conceptualization, Investigation, Methodology, Software, Writing – Review & Editing Catalina Turcu Roles: Investigation, Methodology, Writing – Review & Editing Emma Hutchinson Roles: Investigation, Methodology, Writing – Review & Editing James Milner Roles: Methodology, Writing – Review & Editing Melanie Crane Roles: Methodology, Writing – Review & Editing Andy Haines Roles: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing – Review & Editing Michael Davies Roles: Conceptualization, Funding Acquisition, Methodology, Writing – Review & Editing Paul Wilkinson Roles: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing – Review & Editing Abstract Cities produce more than 70% of global greenhouse gas emissions. Action by cities is therefore crucial for climate change mitigation as well as for safeguarding the health and wellbeing of their populations under climate change. Many city governments have made ambitious commitments to climate change mitigation and adaptation and implemented a range of actions to address them. However, a systematic record and synthesis of the findings of evaluations of the effect of such actions on human health and wellbeing is currently lacking. This, in turn, impedes the development of robust knowledge on what constitutes high-impact climate actions of benefit to human health and wellbeing, which can inform future action plans, their implementation and scale-up. The development of a systematic record of studies reporting climate and health actions in cities is made challenging by the broad landscape of relevant literature scattered across many disciplines and sectors, which is challenging to effectively consolidate using traditional literature review methods. This protocol reports an innovative approach for the systematic development of a database of studies of climate change mitigation and adaptation actions implemented in cities, and their benefits (or disbenefits) for human health and wellbeing, derived from peer-reviewed academic literature. Our approach draws on extensive tailored search strategies and machine learning methods for article classification and tagging to generate a database for subsequent systematic reviews addressing questions of importance to urban decision-makers on climate actions in cities for human health and wellbeing